An Introduction to Bayesian Optimization
Target Audience: Business Professionals in Logistics
Duration: 30 Minutes
Interactive Experience: Click, Explore, Learn
Welcome to Smart Optimization for the Real World
By the end of this session, you will:
Spot areas where traditional ‘trial and error’ is too slow or expensive
Understand how smart optimization finds solutions with fewer tests
Understand ‘smart predictors’ and ‘decision-makers’ for data science conversations
Grasp why exploration vs exploitation balance drives innovation
Interactive demos ahead - get ready to click and explore!
The Challenge
2 minutes
Smart Strategy
7 minutes
The Loop
4 minutes
Real Impact
2 minutes
In logistics, every test costs time, fuel, and money.
How do we find the best solutions with the fewest expensive trials?
Think: New route planning software
Every evaluation costs:
❌ You can’t run millions of tests!
You want the best result, but testing every combination is impossible.
Random guesses are inefficient. We need a smarter strategy.
Next: How Bayesian Optimization solves this intelligently →
Like having an intelligent assistant that gets smarter with every test
(Surrogate Model)
Learns from your test results to predict what might happen everywhere else
Like an experienced manager predicting route performance
⟷
(Acquisition Function)
Decides where to run your next expensive test for maximum value
Balances exploring new areas vs improving known good areas
Watch how the Smart Predictor becomes more accurate with each test
Chooses the next test to either improve the best-known result or reduce uncertainty in a new area.
Run initial tests
Update belief
Next test location
Run experiment
Learn & iterate
Notice how the algorithm first explores uncertain areas, then exploits promising regions to find the optimum faster than random testing!
Reducing expensive trials = Efficiency + Cost Savings + Innovation
Find the best settings for demand forecasting and delivery time estimation models
Fine-tune vehicle routing algorithms to minimize fuel costs and delivery times
Optimize robot movement and sorting policies using efficient simulations
Find optimal distribution center locations balancing costs and service levels
When each test costs time and money,
smart optimization isn’t just nice to have—it’s essential for staying competitive
AI now creates entirely new optimization approaches
AI Writes Code: LLM generates new decision-making strategies
Auto-Testing: System tests each strategy on different problems
Evolution: Best strategies survive and improve
Custom strategies that work better than standard approaches
Source: Aglietti et al. (2024). Funbo: Discovering acquisition functions for bayesian optimization with funsearch. arXiv:2406.04824.
How FunBO Works: AI proposes code, tests it, evolves solutions
Bayesian Optimization = Smart Predictions + Intelligent Decisions
🎤
Ready to explore how Bayesian Optimization can transform your logistics operations?
Let’s discuss your specific challenges and opportunities!
Contact Information
Your Data Science Team | your-team@company.com
Generated with Bayesian Optimization interactive demos